thinkair: the power of mobile cloud computing · 2018. 1. 4. · thinkair: the power of mobile...

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ThinkAir: the power of mobile cloud computing Andrius Aucinas In collaboration with: Sokol Kosta, Pan Hui, Richard Mortier, Xinwen Zhang What it is ThinkAir is a mobile cloud computing framework which allows developers to increase the power of smartphones by using code offloading. It is built for the Android platform and using VM technology it can bridge mobile devices to any cloud computing provider to augment the device’s resources. ThinkAir enables: automatic computation offloading from mobile devices to the cloud performing on-demand resource allocation, and exploiting parallelism by dynamically creating, resuming, and destroy- ing VMs when needed. Example applications signature 1 signature 2 signature 3 signature N All solutions to the N-Queens Puzzle Number of faces in a picture and duplicate photos Count viruses in a filesystem The ThinkAir framework Preliminary results Phone: app executed entirely on the phone WiFi Local: code offloaded to "private cloud" WiFi: code offloaded to public cloud using WiFi 3G: code offloaded to public cloud using 3G Left to right: Energy consumed by each component on the phone for 8-queens puzzle in different scenarios, Time taken and Energy consumed on the phone executing 8-queens puzzle using N = {1, 2, 4, 8} clones. Left to right: Energy consumed by each component on the phone for Face detection in different scenarios, Time taken and Energy consumed on the phone executing Face detection using N = {1, 2, 4, 8} clones. On-demand resource allocation ThinkAir Framework app Phone Cloud Virtualization Internet - x86 app ThinkAir Framework app app detectFaces() app ThinkAir Framework app - x86 app ThinkAir Framework app - x86 app ThinkAir Framework app - x86 app app app app app app app return result Work in progress and further directions More accurate resource usage estimation and prediction using symbolic evaluation techniques Focus on offloading for real-time, interactive applications - low latency requirement Domain-specific offloading optimisations: image processing, streaming video information ex- traction (for AR) Development of simple to use developer interface to the efficient offloading solutions Related works [1] Eduardo Cuervo, Aruna Balasubramanian, Dae-ki Cho, Alec Wolman, Stefan Saroiu, Ranveer Chandra, and Paramvir Bahl. MAUI: making smartphones last longer with code offload In MobiSys ’10: Proceedings of the 8th international conference on Mobile systems, applica- tions, and services. 2010. [2] Byung-Gon Chun, Sunghwan Ihm, Petros Maniatis, Mayur Naik, and Ashwin Patti. CloneCloud: Elastic Execution between Mobile Device and Cloud In Pro- ceedings of the 6th European Conference on Computer Sys- tems (EuroSys 2011).

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Page 1: ThinkAir: the power of mobile cloud computing · 2018. 1. 4. · ThinkAir: the power of mobile cloud computing Andrius Aucinas In collaboration with: Sokol Kosta, Pan Hui, Richard

ThinkAir: the power of mobile cloud computingAndrius AucinasIn collaboration with: Sokol Kosta, Pan Hui, Richard Mortier, Xinwen Zhang

What it isThinkAir is a mobile cloud computing framework which allows developers to increase the power of smartphones by using

code offloading. It is built for the Android platform and using VM technology it can bridge mobile devices to any cloud

computing provider to augment the device’s resources.

ThinkAir enables:

• automatic computation offloading from mobile devices to the cloud

• performing on-demand resource allocation, and exploiting parallelism by dynamically creating, resuming, and destroy-

ing VMs when needed.

Example applications

Find all the solutions of the N-Queens Puzzle.

Count the number of faces in a

picture and detect

duplicated photos.

signature 1

signature 2

signature 3

signature N

Return the number of

viruses found.

All solutions to the

N-Queens Puzzle

Number of faces in a picture

and duplicate photos

Count viruses in a filesystem

The ThinkAir framework

Preliminary resultsPhone: app executed entirely on the phone

WiFi Local: code offloaded to "private cloud"

WiFi: code offloaded to public cloud using WiFi

3G: code offloaded to public cloud using 3G

Left to right: Energy consumed by each component on the phone for 8-queens puzzle in

different scenarios, Time taken and Energy consumed on the phone executing 8-queens puzzle

using N = {1, 2, 4, 8} clones.

Left to right: Energy consumed by each component on the phone for Face detection in different

scenarios, Time taken and Energy consumed on the phone executing Face detection using N = {1,

2, 4, 8} clones.

On-demand resource allocation

ThinkAir Framework

app

PhoneC

loud

VirtualizationInternet

- x86

app

ThinkAir Framework

appapp

detectFaces()

app

ThinkAir Framework

app

- x86

app

ThinkAir Framework

app

- x86

app

ThinkAir Framework

app

- x86

app

app

app

appappapp

app

returnresult

Work in progress and further directionsMore accurate resource usage estimation and prediction using symbolic evaluation techniques

Focus on offloading for real-time, interactive applications - low latency requirement

Domain-specific offloading optimisations: image processing, streaming video information ex-

traction (for AR)

Development of simple to use developer interface to the efficient offloading solutions

Related works[1] Eduardo Cuervo, Aruna Balasubramanian, Dae-ki

Cho, Alec Wolman, Stefan Saroiu, Ranveer Chandra,

and Paramvir Bahl. MAUI: making smartphones last

longer with code offload In MobiSys ’10: Proceedings of

the 8th international conference on Mobile systems, applica-

tions, and services. 2010.

[2] Byung-Gon Chun, Sunghwan Ihm, Petros Maniatis,

Mayur Naik, and Ashwin Patti. CloneCloud: Elastic

Execution between Mobile Device and Cloud In Pro-

ceedings of the 6th European Conference on Computer Sys-

tems (EuroSys 2011).